What users are saying about
32 Ratings
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Score 7.8 out of 100
30 Ratings
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Score 8.1 out of 100

Likelihood to Recommend

KNIME Analytics Platform

If you have a team of engineers or data scientists who do not like to code, KNIME can be a good platform to build quick and dirty pipelines. However if you are moving away from R&D to deployment, KNIME lacks the scalability compared to Python or R itself. When deploying, you can choose to output json or use their native front end from KNIME Server, but KNIME Server is not free.
Ivan Cui | TrustRadius Reviewer

TensorFlow

TensorFlow is great for most deep learning purposes. This is especially true in two domains:1. Computer vision: image classification, object detection and image generation via generative adversarial networks2. Natural language processing: text classification and generation.The good community support often means that a lot of off-the-shelf models can be used to prove a concept or test an idea quickly. That, and Google's promotion of Colab means that ideas can be shared quite freely. Training, visualizing and debugging models is very easy in TensorFlow, compared to other platforms (especially the good old Caffe days).In terms of productionizing, it's a bit of a mixed bag. In our case, most of our feature building is performed via Apache Spark. This means having to convert Parquet (columnar optimized) files to a TensorFlow friendly format i.e., protobufs. The lack of good JVM bindings mean that our projects end up being a mix of Python and Scala. This makes it hard to reuse some of the tooling and support we wrote in Scala. This is where MXNet shines better (though its Scala API could do with more work).
Anonymous | TrustRadius Reviewer

Feature Rating Comparison

Platform Connectivity

KNIME Analytics Platform
7.4
TensorFlow
Connect to Multiple Data Sources
KNIME Analytics Platform
8.5
TensorFlow
Extend Existing Data Sources
KNIME Analytics Platform
7.2
TensorFlow
Automatic Data Format Detection
KNIME Analytics Platform
7.8
TensorFlow
MDM Integration
KNIME Analytics Platform
6.0
TensorFlow

Data Exploration

KNIME Analytics Platform
5.3
TensorFlow
Visualization
KNIME Analytics Platform
5.0
TensorFlow
Interactive Data Analysis
KNIME Analytics Platform
5.6
TensorFlow

Data Preparation

KNIME Analytics Platform
6.1
TensorFlow
Interactive Data Cleaning and Enrichment
KNIME Analytics Platform
7.0
TensorFlow
Data Transformations
KNIME Analytics Platform
7.0
TensorFlow
Data Encryption
KNIME Analytics Platform
4.7
TensorFlow
Built-in Processors
KNIME Analytics Platform
5.9
TensorFlow

Platform Data Modeling

KNIME Analytics Platform
5.6
TensorFlow
Multiple Model Development Languages and Tools
KNIME Analytics Platform
6.5
TensorFlow
Automated Machine Learning
KNIME Analytics Platform
4.5
TensorFlow
Single platform for multiple model development
KNIME Analytics Platform
5.7
TensorFlow
Self-Service Model Delivery
KNIME Analytics Platform
5.9
TensorFlow

Model Deployment

KNIME Analytics Platform
5.2
TensorFlow
Flexible Model Publishing Options
KNIME Analytics Platform
5.6
TensorFlow
Security, Governance, and Cost Controls
KNIME Analytics Platform
4.7
TensorFlow

Pros

KNIME Analytics Platform

  • KNIME works better than most tools for ETL functions.
  • Easy to track the different steps
  • Easy to isolate and fix specific workflow steps.
Anonymous | TrustRadius Reviewer

TensorFlow

  • A vast library of functions for all kinds of tasks - Text, Images, Tabular, Video etc.
  • Amazing community helps developers obtain knowledge faster and get unblocked in this active development space.
  • Integration of high-level libraries like Keras and Estimators make it really simple for a beginner to get started with neural network based models.
Nitin Pasumarthy | TrustRadius Reviewer

Cons

KNIME Analytics Platform

  • Visualization can be improved further though it has been better with new versions, with a lot of scope available. However, connectivity to Tableau somehow overcomes this. Also, skilled resources are difficult to find for KNIME, due to other solutions having better penetration.
  • Knowledge of R/Python is required to fully use the statistical analysis (rather than just data mining). Also, memory usage is a problematic issue sometimes.
  • Not enough domain usage experience can be shared between KNIME users as well.
Rohit Narang | TrustRadius Reviewer

TensorFlow

  • RNNs are still a bit lacking, compared to Theano.
  • Cannot handle sequence inputs
  • Theano is perhaps a bit faster and eats up less memory than TensorFlow on a given GPU, perhaps due to element-wise ops. Tensorflow wins for multi-GPU and “compilation” time.
Nisha murthy | TrustRadius Reviewer

Likelihood to Renew

KNIME Analytics Platform

KNIME Analytics Platform 8.0
Based on 1 answer
I am happy with the product. It provides the required functionality.
Anonymous | TrustRadius Reviewer

TensorFlow

No score
No answers yet
No answers on this topic

Usability

KNIME Analytics Platform

KNIME Analytics Platform 8.0
Based on 1 answer
It performs all the required functions.
Anonymous | TrustRadius Reviewer

TensorFlow

TensorFlow 9.0
Based on 1 answer
Support of multiple components and ease of development.
Anupam Mittal | TrustRadius Reviewer

Support Rating

KNIME Analytics Platform

KNIME Analytics Platform 6.7
Based on 4 answers
Since it is relatively new, there has not developed a vast previously asked/frequently asked questions library that comes up when you google an issue you come across with. This will happen only in time, and as the community grows. Because of the same reason, the community is not big. Consequently, it is possible not to receive good, fast responses to asked questions in community hubs and forums.
Anonymous | TrustRadius Reviewer

TensorFlow

TensorFlow 9.3
Based on 2 answers
Community support for TensorFlow is great. There's a huge community that truly loves the platform and there are many examples of development in TensorFlow. Often, when a new good technique is published, there will be a TensorFlow implementation not long after. This makes it quick to ally the latest techniques from academia straight to production-grade systems. Tooling around TensorFlow is also good. TensorBoard has been such a useful tool, I can't imagine how hard it would be to debug a deep neural network gone wrong without TensorBoard.
Anonymous | TrustRadius Reviewer

Implementation Rating

KNIME Analytics Platform

KNIME Analytics Platform 8.0
Based on 1 answer
No answer on this topic is available.

TensorFlow

TensorFlow 8.0
Based on 1 answer
Use of cloud for better execution power is recommended.
Anupam Mittal | TrustRadius Reviewer

Alternatives Considered

KNIME Analytics Platform

KNIME is a lower price point and has strong cross platform capabilities. Other platforms are locked to a specific operating system and cost in some cases substantially more, making them less good choices for smaller businesses that still need basic data unification. The fact that KNIME is OS-independent is a big positive.
Christopher Penn | TrustRadius Reviewer

TensorFlow

Keras is built on top of TensorFlow, but it is much simpler to use and more Python style friendly, so if you don't want to focus on too many details or control and not focus on some advanced features, Keras is one of the best options, but as far as if you want to dig into more, for sure TensorFlow is the right choice
Anonymous | TrustRadius Reviewer

Return on Investment

KNIME Analytics Platform

  • Lowest TCO compared to other tools
  • Accelerates analysis - the analysts can dedicate more time to analysis itself, not to data preparation
Viktor Mulac | TrustRadius Reviewer

TensorFlow

  • Learning is s bit difficult takes lot of time.
  • Developing or implementing the whole neural network is time consuming with this, as you have to write everything.
  • Once you have learned this, it make your job very easy of getting the good result.
Shambhavi Jha | TrustRadius Reviewer

Pricing Details

KNIME Analytics Platform

General

Free Trial
Free/Freemium Version
Premium Consulting/Integration Services
Entry-level set up fee?
No

TensorFlow

General

Free Trial
Free/Freemium Version
Premium Consulting/Integration Services
Entry-level set up fee?
No

Rating Summary

Likelihood to Recommend

KNIME Analytics Platform
7.8
TensorFlow
8.4

Likelihood to Renew

KNIME Analytics Platform
8.0
TensorFlow

Usability

KNIME Analytics Platform
8.0
TensorFlow
9.0

Support Rating

KNIME Analytics Platform
6.7
TensorFlow
9.3

Implementation Rating

KNIME Analytics Platform
8.0
TensorFlow
8.0

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